A universal 3D imaging sensor on a silicon photonics platform
A universal 3D imaging sensor on a silicon photonics platform
Accurate 3D imaging is essential for machines to map and interact with the physical world. While numerous 3D imaging technologies exist, each addressing niche applications with varying degrees of success, none have achieved the breadth of applicability and impact that digital image sensors have achieved in the 2D imaging world. A large-scale two-dimensional array of coherent detector pixels operating as a light detection and ranging (LiDAR) system could serve as a universal 3D imaging platform. Such a system would offer high depth accuracy and immunity to interference from sunlight, as well as the ability to directly measure the velocity of moving objects. However, due to difficulties in providing electrical and photonic connections to every pixel, previous systems have been restricted to fewer than 20 pixels. Here, we demonstrate the first large-scale coherent detector array consisting of 512 (32 × 16) pixels, and its operation in a 3D imaging system. Leveraging recent advances in the monolithic integration of photonic and electronic circuits, a dense array of optical het25 erodyne detectors is combined with an integrated electronic readout architecture, enabling straightforward scaling to arbitrarily large arrays. Meanwhile, two-axis solid-state beam steering eliminates any tradeoff between field of view and range. Operating at the quantum noise limit, our system achieves an accuracy of 3.1 mm at a distance of 75 metres using only 4 mW of light, an order of magnitude more accurate than existing solid-state systems at such ranges. Future reductions of pixel size using state-of-the-art components could yield resolutions in excess of 20 megapixels for arrays the size of a consumer camera sensor. This result paves the way for the development and proliferation of low cost, compact, and high performance 3D imaging cameras, enabling new applications from robotics and autonomous navigation to augmented reality and healthcare.
silicon photonics, LiDAR, 3D imaging
256–261
Rogers, Christopher
f13efa08-72fa-4f29-afc2-3de64c6c691f
Piggott, Alexander
8a9f60e1-94c9-4350-a5e8-35b97804aed7
Thomson, David
17c1626c-2422-42c6-98e0-586ae220bcda
Wiser, Robert
8abaa768-b6c0-4661-9563-cf1bb1b4099a
Opris, Ion
5fefeb75-4ac5-4ff9-9392-e40608348f03
Fortune, Steven
ffdb2288-4d4d-40a0-b8cb-db7135f1be25
Compston, Andrew
f1d582ee-27c6-433e-ae1c-efd0ffbb20fe
Gondarenko, Alexander
aa61e761-418a-4aac-935b-ff1f7b9553fd
Meng, Fanfan
9b5e8c83-a510-4eb0-87ff-c768345ba07d
Chen, Xia
64f6ab92-ca11-4489-8c03-52bc986209ae
Reed, Graham
ca08dd60-c072-4d7d-b254-75714d570139
Nicolaescu, Remus
1a78069d-01b3-48f7-8b01-7dfde2742f59
Rogers, Christopher
f13efa08-72fa-4f29-afc2-3de64c6c691f
Piggott, Alexander
8a9f60e1-94c9-4350-a5e8-35b97804aed7
Thomson, David
17c1626c-2422-42c6-98e0-586ae220bcda
Wiser, Robert
8abaa768-b6c0-4661-9563-cf1bb1b4099a
Opris, Ion
5fefeb75-4ac5-4ff9-9392-e40608348f03
Fortune, Steven
ffdb2288-4d4d-40a0-b8cb-db7135f1be25
Compston, Andrew
f1d582ee-27c6-433e-ae1c-efd0ffbb20fe
Gondarenko, Alexander
aa61e761-418a-4aac-935b-ff1f7b9553fd
Meng, Fanfan
9b5e8c83-a510-4eb0-87ff-c768345ba07d
Chen, Xia
64f6ab92-ca11-4489-8c03-52bc986209ae
Reed, Graham
ca08dd60-c072-4d7d-b254-75714d570139
Nicolaescu, Remus
1a78069d-01b3-48f7-8b01-7dfde2742f59
Rogers, Christopher, Piggott, Alexander, Thomson, David, Wiser, Robert, Opris, Ion, Fortune, Steven, Compston, Andrew, Gondarenko, Alexander, Meng, Fanfan, Chen, Xia, Reed, Graham and Nicolaescu, Remus
(2021)
A universal 3D imaging sensor on a silicon photonics platform.
Nature, 590, .
(doi:10.1038/s41586-021-03259-y).
Abstract
Accurate 3D imaging is essential for machines to map and interact with the physical world. While numerous 3D imaging technologies exist, each addressing niche applications with varying degrees of success, none have achieved the breadth of applicability and impact that digital image sensors have achieved in the 2D imaging world. A large-scale two-dimensional array of coherent detector pixels operating as a light detection and ranging (LiDAR) system could serve as a universal 3D imaging platform. Such a system would offer high depth accuracy and immunity to interference from sunlight, as well as the ability to directly measure the velocity of moving objects. However, due to difficulties in providing electrical and photonic connections to every pixel, previous systems have been restricted to fewer than 20 pixels. Here, we demonstrate the first large-scale coherent detector array consisting of 512 (32 × 16) pixels, and its operation in a 3D imaging system. Leveraging recent advances in the monolithic integration of photonic and electronic circuits, a dense array of optical het25 erodyne detectors is combined with an integrated electronic readout architecture, enabling straightforward scaling to arbitrarily large arrays. Meanwhile, two-axis solid-state beam steering eliminates any tradeoff between field of view and range. Operating at the quantum noise limit, our system achieves an accuracy of 3.1 mm at a distance of 75 metres using only 4 mW of light, an order of magnitude more accurate than existing solid-state systems at such ranges. Future reductions of pixel size using state-of-the-art components could yield resolutions in excess of 20 megapixels for arrays the size of a consumer camera sensor. This result paves the way for the development and proliferation of low cost, compact, and high performance 3D imaging cameras, enabling new applications from robotics and autonomous navigation to augmented reality and healthcare.
Text
A_universal_3D_imaging_sensor_on_a_silicon_photonics_platform_compress
- Accepted Manuscript
Available under License Other.
More information
Accepted/In Press date: 16 November 2020
e-pub ahead of print date: 10 February 2021
Keywords:
silicon photonics, LiDAR, 3D imaging
Identifiers
Local EPrints ID: 481569
URI: http://eprints.soton.ac.uk/id/eprint/481569
ISSN: 1476-4687
PURE UUID: 130fd9bd-4e8c-4c02-bb92-01ae510d16f5
Catalogue record
Date deposited: 04 Sep 2023 16:34
Last modified: 16 Mar 2024 10:09
Export record
Altmetrics
Contributors
Author:
Christopher Rogers
Author:
Alexander Piggott
Author:
David Thomson
Author:
Robert Wiser
Author:
Ion Opris
Author:
Steven Fortune
Author:
Andrew Compston
Author:
Alexander Gondarenko
Author:
Fanfan Meng
Author:
Xia Chen
Author:
Graham Reed
Author:
Remus Nicolaescu
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics